Multiple Pursuers TrailMax Algorithm for Dynamic Environments

Azizkhon Afzalov, Ahmad Lotfi, Benjamin Inden, Mehmet Aydin

Abstract

Multi-agent multi-target search problems, where the targets are capable of movement, require sophisticated algorithms for near-optimal performance. While there are several algorithms for agent control, comparatively less attention has been paid to near-optimal target behaviours. Here, a state-of-the-art algorithm for targets to avoid a single agent called TrailMax has been adapted to work within a multiple agents and multiple targets framework. The aim of the presented algorithm is to make the targets avoid capture as long as possible, if possible until timeout. Empirical analysis is performed on grid-based gaming benchmarks. The results suggest that Multiple Pursuers TrailMax reduces the agent success rate by up to 15% as compared to several previously used target control algorithms and increases the time until capture in successful runs.

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Paper Citation


in Harvard Style

Afzalov A., Lotfi A., Inden B. and Aydin M. (2021). Multiple Pursuers TrailMax Algorithm for Dynamic Environments.In Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-484-8, pages 437-443. DOI: 10.5220/0010392404370443


in Bibtex Style

@conference{icaart21,
author={Azizkhon Afzalov and Ahmad Lotfi and Benjamin Inden and Mehmet Aydin},
title={Multiple Pursuers TrailMax Algorithm for Dynamic Environments},
booktitle={Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2021},
pages={437-443},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010392404370443},
isbn={978-989-758-484-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Multiple Pursuers TrailMax Algorithm for Dynamic Environments
SN - 978-989-758-484-8
AU - Afzalov A.
AU - Lotfi A.
AU - Inden B.
AU - Aydin M.
PY - 2021
SP - 437
EP - 443
DO - 10.5220/0010392404370443